Sampled-data state estimation for delayed Markovian jump neural networks based on passive theory

2016 ◽  
Author(s):  
N. Gunasekaran ◽  
M. Syed Ali
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Sampled Data ◽  
Markovian Jump ◽  
Passive Theory ◽  
Markovian Jump Neural Networks

Asynchronous finite-time state estimation for semi-Markovian jump neural networks with randomly occurred sensor nonlinearities

2021 ◽  
Vol 432 ◽  
pp. 240-249
Author(s):  
Yao Wang ◽  
Shengyuan Xu ◽  
Yongmin Li ◽  
Yuming Chu ◽  
Zhengqiang Zhang
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Finite Time ◽  
Markovian Jump ◽  
Markovian Jump Neural Networks

State estimation for uncertain Markovian jump neural networks with mixed delays

2016 ◽  
Vol 182 ◽  
pp. 82-93 ◽  
Author(s):  
Qian Li ◽  
Qingxin Zhu ◽  
Shouming Zhong ◽  
Xiaomei Wang ◽  
Jun Cheng
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Mixed Delays ◽  
Markovian Jump ◽  
Markovian Jump Neural Networks

scholarly journals Synchronization of Markovian Jump Neural Networks for Sampled Data Control Systems With Additive Delay Components:Analysis of Image Encryption Technique

2021 ◽  
Author(s):  
Tamil Thendral M ◽  
Ganesh Babu T.R ◽  
Chandrasekar A ◽  
Yang Cao
Keyword(s):  
Neural Networks ◽  
Control Systems ◽  
Image Encryption ◽  
Tuning Parameter ◽  
Modern World ◽  
Sampled Data ◽  
Markovian Jump ◽  
Data Control ◽  
Sampled Data Control ◽  
Markovian Jump Neural Networks

In an modern world, image encryption played an vital role to prevent our data from illegal abuser entrée. Based on this, in this paper the Markovian jump neural networks for synchronization of sampled-data control systems with {two additive delay components are used on the looped functional method and its direct application is applied in image encryption.} Meanwhile, $x({t_{\chi}} )$ and $x({t_{\chi+1}})$ denotes the information states with tuning parameter and a few slack variable which is introduced in the derived result. Furthermore, the sampled-data controller is intended both the present and delayed state information, to enroll the control performance and flexibility. Finally by using the new technique, the several examples are highlighted in the numerical section and also the effectiveness of an image encryption is studied.

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